Chemicals and materials / Polymer materials
Covestro: Automated machine learning monitoring of critical plant components and process steps
- Company
- Covestro
- Country
- Germany
- Adoption stage
- In operation
- Source published
- Date basis
- The date the source was published. It can differ from the date adoption started.
- How the source was checked
- Read the full source text
The work problem
According to the AI transformation section of the 2025 annual report Covestro published on February 26, 2026, companies face the challenge of boosting efficiency while reducing costs in increasingly complex production environments, and unplanned downtime costs manufacturing companies millions of dollars each year. Manual processes and routine customer service also tie up resources that could be used for innovation and problem solving.
Technology and data
Covestro uses machine learning to automatically monitor critical plant components and process steps, and the system triggers an alert as soon as critical production parameters change. This detailed plant monitoring is being rolled out globally across nine sites. Covestro is also transferring insights from the autonomous production line that has been running at its Dormagen operations since June 2024 to other production facilities.
Results
According to the report, Covestro achieved increased production and cost avoidance opportunities worth tens of millions of euros in 2025 alone through this plant monitoring. Pilot projects to transfer the autonomous production line insights have started at seven sites worldwide, and the company sees additional potential worth tens of millions of euros there as well.
Limits and open questions
The procedure people follow after an alert, the effect at each site and the exact amounts are not in the report.
Sources
- AI Transformation Delivers Measurable Impactannualreport.covestro.com, Accessed
Compiled from public sources. These are not results from ATF Works customers.